Build
Your competitors shipped generative AI. You're still in evaluation.
GenAI products shipped
Quality threshold met
Weeks to launch
Trusted by teams at
The Problem
Your roadmap has generative features on it, but your team hasn't built prompt engineering at scale, content safety, quality control, or the cost discipline a production generative workload needs.
While you run another internal proof of concept, a smaller competitor already ships AI-generated content as a feature your shared customers love. The window to lead is closing fast.
What you get
Overview
Most teams treat generative AI as a toy until a competitor ships it as a product. We build the production version so you're not playing catch-up - with safety, cost controls, and quality gates wired in from the first prompt.
Generative AI is easy to prototype and hard to ship. The gap between a playground demo and a real feature is content safety, quality consistency, cost control, brand alignment, and a UX users actually trust.
We build generative features as controlled production systems. Every output passes quality gates, content safety filters, cost tracking, and feedback loops that improve generation quality over time.
You get generative capabilities your users trust and your team can operate - not a feature that produces unpredictable outputs and burns through API credits.
Experience Signal
Shipped 25+ generative AI systems across SaaS, commerce, and media with production-grade quality and safety controls. 12 weeks is our default, not our stretch goal.
What we build
Brand-voiced writing, email copy, blog drafts, and social posts generated inside your product with tone controls and a human review queue.
Product imagery, marketing visuals, and design variants generated with brand alignment, style controls, and moderation built in.
Catalog-wide generation pipelines that turn attributes and images into SEO-ready copy in every category, batchable across millions of SKUs.
Statistically representative data for model training and testing, with privacy guarantees and distribution checks on every batch.
In-product copilots for designers, marketers, and editors - generation suggestions, variant iteration, and style-matched output.
Short-form video, voiceover, and audio generation pipelines for marketing, product explainer, and personalization use cases.
Production-grade prompt chains, retrieval augmentation, and output validators that keep generation quality stable as models update.
Content safety classifiers, cost budgets, quality scoring, and real-time monitoring so generative features stay on-brand and on-budget.
Fit
Good fit
Not the right fit
Process
We define output requirements, quality criteria, and safety constraints. Then we benchmark candidate models across quality, speed, and cost before picking the stack.
Deliverables
We design the generation pipeline - prompt chains, output validation, safety filters, and feedback loops. Evaluation harnesses get built before any production code ships.
Deliverables
We build the generative features into your product, instrument quality and cost tracking, and tune prompts and pipelines against real usage data every week.
Deliverables
We finalize content safety controls, stress-test edge cases, deploy to production, and hand the prompt and quality controls over to your team with a runbook.
Deliverables
12-week end-to-end delivery of one production generative feature with quality, safety, and cost controls.
Best forTeams shipping their first generative feature with production quality requirements.
GPT-5
OpenAI
General-purpose text generation - drafts, edits, rewrites, and structured output.
Claude Sonnet 4.6
Anthropic
High-volume production text generation where cost per output has to stay predictable.
Claude Opus 4.6
Anthropic
Long-context generation over briefs, style guides, and large source documents.
Stable Diffusion 3
Stability AI
Image generation with fine-grained style controls and brand alignment.
DALL-E 3
OpenAI
Fast iteration on marketing imagery and product visuals with strong prompt adherence.
ElevenLabs
ElevenLabs
Voiceover, audio generation, and personalized narration for product and marketing use cases.
Use Cases
A marketing platform wants to ship AI-powered content creation - blog drafts, social posts, and email copy - directly inside its product without blowing up support.
How we build it
We build a generation pipeline with brand voice tuning, multi-format templates, tone controls, and a human review queue. Quality is tracked per content type with user feedback loops.
Outcome
Users generate 5x more content. Average creation time drops from 45 minutes to 8 minutes per piece.
A marketplace with 50,000+ products needs consistent, SEO-optimized descriptions. Manual writing covered 20% of the catalog and that was it.
How we build it
We build a generation system that produces descriptions from product attributes and images, with category-specific templates, SEO optimization, and batch processing for full catalog coverage.
Outcome
Full catalog coverage in 3 weeks. Organic traffic to product pages climbs 25% over 2 months.
A healthcare AI team needs more training data for a rare-condition classifier but can't touch more patient records because of privacy constraints.
How we build it
We build a synthetic data pipeline that generates statistically representative samples, preserves distribution patterns, and runs re-identification checks on every batch.
Outcome
Training dataset grows 10x. Model accuracy on rare conditions climbs from 72% to 89%.
What clients say
I spent years at Amazon fighting static surveys. RaftLabs built a working prototype in four days that already outperformed every survey tool I'd used. Twelve weeks later we had a full SaaS that product teams actually want to use.
Founder
Ex-Amazon PM - Perceptional
We went from text surveys that nobody finished to AI phone interviews that people actually enjoy. The voice agents handle the whole conversation, and the analytics tell us what we need to know without reading a single transcript.
Cherian Koshy
Behavioral Strategist - USA Today Bestselling Author
Proof
Deeper insights
Concept to launch
“Working prototype in four days. Full SaaS in twelve weeks.”
Read case studyTo production
Call reach
“Text surveys nobody finished became phone interviews people enjoy.”
Read case studyIndustries
Content generation, campaign copy, and creative variants for marketing teams that can't keep up with volume.
ExploreProduct descriptions, catalog imagery, and on-site copy generated at catalog scale with SEO controls.
ExploreListing descriptions, guest communications, and multilingual content for properties at scale.
ExploreLesson generation, practice problems, and personalized explanations grounded in your curriculum.
ExploreSynthetic datasets and patient-education content with the privacy and safety controls the industry demands.
ExploreReport generation, compliance-aware summaries, and customer communications that pass review.
ExploreWe work with OpenAI (GPT-5, DALL-E 3), Anthropic (Claude Opus and Sonnet 4.6), Stability AI (Stable Diffusion 3), ElevenLabs, Replicate, and open-source models. Model choice depends on your quality, cost, and safety requirements - we benchmark before we pick.
Related Services
Next Step
We take generative features from playground demo to production, with safety controls, cost management, and quality consistency baked in from day one.